Triple
T30574069
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Mother (novel) |
E778194
|
entity |
| Predicate | targetSocialGroup |
P10541
|
FINISHED |
| Object | industrial working class |
—
|
LITERAL FINISHED |
How this triple was built (2 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: industrial working class | Statement: [Mother (novel), targetSocialGroup, industrial working class]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: targetSocialGroup Context triple: [Mother (novel), targetSocialGroup, industrial working class]
-
A.
targetsGroup
chosen
Indicates that an action, influence, or effect is directed toward a specific group as its intended recipient or focus.
-
B.
hasSocialGroup
Indicates that an entity belongs to, is associated with, or participates in a particular social group or community.
-
C.
socialGroupInvolved
Indicates that a particular social group participates in, is affected by, or is otherwise involved in the specified event or situation.
-
D.
socialGroupBenefited
Indicates that a particular social group gains an advantage, improvement, or positive impact as a result of an action, event, or resource.
-
E.
groups
Indicates that one entity organizes, clusters, or associates multiple entities together as members of a collective set or category.
- F. None of above.
Provenance (3 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69f2249f8c148190ae7eb3912cde112a |
completed | April 29, 2026, 3:32 p.m. |
| NER | Named-entity recognition | batch_69fd4d1854988190be093b103a681798 |
completed | May 8, 2026, 2:40 a.m. |
| PD | Predicate disambiguation | batch_69fd4c8d1a188190897c24527337814a |
completed | May 8, 2026, 2:38 a.m. |
Created at: April 29, 2026, 8:22 p.m.